Pathfinders in the Sky: Formal Decision-Making Models for Collaborative Air Traffic Control in Convective Weather

TL;DR

This paper develops formal decision-making models for collaborative air traffic control involving pathfinder aircraft in convective weather, analyzing system dynamics, acceptance behaviors, and resilience through empirical FAA data.

Contribution

It introduces stochastic models capturing operational dynamics and decision strategies for pathfinders, filling a research gap in multi-agent air traffic management under weather disruptions.

Findings

Pathfinder operations are significant in real-world air traffic control.

Selfless behavior and uncertainty impact system resilience.

Empirical FAA data informs model calibration and validation.

Abstract

Air traffic can be significantly disrupted by weather. Pathfinder operations involve assigning a designated aircraft to assess whether airspace that was previously impacted by weather can be safely traversed through. Despite relatively routine use in air traffic control, there is little research on the underlying multi-agent decision-making problem. We seek to address this gap herein by formulating decision models to capture the operational dynamics and implications of pathfinders. Specifically, we construct a Markov chain to represent the stochastic transitions between key operational states (e.g., pathfinder selection). We then analyze its steady-state behavior to understand long-term system dynamics. We also propose models to characterize flight-specific acceptance behaviors (based on utility trade-offs) and pathfinder selection strategies (based on sequential offer allocations). We then conduct a worst-case scenario analysis that highlights risks from collective rejection and explores how selfless behavior and uncertainty affect system resilience. Empirical analysis of data from the US Federal Aviation Administration demonstrates the real-world significance of pathfinder operations and informs future model calibration.